1. Field of the invention
This invention relates in general to methods and data processing system readable media, and more particularly, to methods of modeling operating parameters and data processing system readable media having software code for carrying out those methods.
2. Description of the Related Art
Selecting prices for thousands of items is a difficult proposition. The current practice indicates that retailers may be over-discounting products, with as many as 25%–30% of items being sold at some price discount. With profit margins so low already (approximately 1.5% is some business sectors), many retail stores may not be able to sustain aggressive price discounting.
Pricing is made difficult by the fact that products interact with each other. Decreasing the price of one juice item to increase traffic may merely result in the cannibalization of a more profitable juice brand (as consumers switch from one brand to the other), without increasing demand for all juice products. Similarly, raising prices may have pronounced consequences across category boundaries, such as decreasing the number of items bought in distant or unrelated categories due to a general reduction in store traffic.
Retailers have long been aware of price-demand interactions and have developed various strategies for coping with these effects. One common strategy is known as “loss leader pricing.” “Loss leaders” are products that are kept at discounted prices because they are known to be high profile, common, and easily comparable between retailers. Typical loss leaders for grocers include milk, bread, eggs, and juice. Loss leaders are presently determined by retailer experience. A problem is correctly identifying which, if any, products are to be loss leaders.
Automated analysis of product interactions has as yet been limited to very small numbers of products, often within the same category. Working with all product interactions is often practically infeasible because of the number of potential interactions that need to be examined. Assuming 100,000 items are examined, there could be 10 billion interactions.
A need exists for a comprehensive approach to modeling retail operations which incorporates knowledge of product interactions, consumer demand, storewide effects and the like. Furthermore, since most retail stores have thousands of items and millions of transactions, a need exists to deal with product interactions in a comprehensive, automated, computationally fast and efficient manner.